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Near-fault ground motions may cause serious damage and consequence of high-speed railway bridges (HSRBs), since their particularly detrimental effects, including the hanging-wall effects and velocity pulse effects. However, the induced seismic demand depends on the complex relationship between natural vibration characteristics of structures and frequent contents of ground motions, leading to the difficulty in attributing to less seismic attenuation or/and the above special effects. This work adopts a framework to select a ground motion suite with a specified near-fault effect by multiple controllable constraints on the target response spectrum. Near-fault effect on seismic demand is visualized and quantified by empirical cumulative distribution functions (ECDFs) and the Kolmogorov-Smirnov test. An ECDF-based method is proposed to develop a bilinear probabilistic seismic demand model (PSDM) to capture the nonlinear relationship between engineering demand parameter (EDP) and intensity measure caused by near-fault effects. In the case study, the hanging-wall effects and the directivity-induced velocity pulse effects are investigated on a simply-supported HSRB. The influence of the two effects on key structural components is examined, in which the demand changes are attributed to one of them. The result shows that the hanging-wall effect amplifies both mean and variance of the seismic demands. Pulse-like records cause sudden increases in demand ECDFs, which are used to determine the transition point in the bilinear PSDMs. The refined PSDMs well capture the nonlinear trend of EDP varying with PGV when considering pulse-like records.

China Railway Track System II (CRTS II) slab ballastless track structure is one of commonly adopted track systems on the high-speed railway bridge, which has been found seismically vulnerable under strong earthquakes. To investigate the earthquake-induced damage mechanism of the CRTS II slab ballastless track structure, a nonlinear numerical model of typical 7-span simply supported bridge–track system was established by the finite element software OpenSees and well calibrated by the test data and relative literatures. The nonlinear time history analysis was employed to calculate seismic responses of bridge and track parts under a suite of 10 seismic records. Results demonstrate that the sliding layer in the track structure is the most damage-prone component, especially at the bridge-subgrade transition section, and the shear alveolar may also sustain earthquake-induced fail. By analyzing the seismic damage mechanism of the track structure, this paper reveals that the nonuniform displacement responses of the girders and friction plate at the bridge-subgrade transition section are main factors that result in the extensive damage of the sliding layer and failure of the shear alveolar. However, the damage of these two components are beneficial to reduce the seismic responses of other components in the track structure and protect them from being damaged. From the perspective of engineering safety, the sliding layer and shear alveolar should be rigorously designed because the residual displacement of the sliding layer increases along with the maximum displacement and the failure of the shear alveolar may make the whole track structure failed.

The main goal of this paper is to perform the safety assessment of high-speed trains (HSTs) on the simply supported bridges (SSBs) under low-level earthquakes, which are frequently encountered by HSTs, utilizing spectral intensity (SI) index. First, the HST’s limit displacements, which are calculated by using the multi-body train model with detailed wheel–rail relationship, varying with train speed, frequency and amplitude of a sinusoidal base excitation are obtained. Then, based on the obtained HST’s limit displacements, the spectral intensity limits (SI_L) graded by the train’s running speed are calculated, and the relationship between the bridge seismic dynamic responses and the train’s running safety was established. Next, the method that utilizes the SI and the SI_L indexes to evaluate the HST’s running safety was proposed and verified by comparing with the evaluation result of the train–track–bridge interaction model. Based on the proposed SI index, the HST’s running safety on the SSBs was evaluated under earthquakes, considering different pier heights and site types. The results showed that the low-frequency components of the ground motions are unfavorable to the HST’s running safety, and the height of bridge piers has a significant impact on running safety.

The influence of track irregularity and deck deformation on the running safety of high-speed railway (HSR) trains is investigated, with emphasis placed on those caused by the creep of continuous prestressed bridges. A bridge model is established with CRTS II ballastless track to account for a train-track-bridge (TTB) system. The creep effect is calculated by the finite element software MIDAS/Civil. The accuracy of the numerical simulation is confirmed by comparing the numerical predictions with field measurements. Considering the stability index of the moving train, the deformation threshold for safe operation of the train is determined. The results show that the initial prestressing stress has a great impact on the residual deformation of the bridge, but the deformation of the rail is less affected by the stiffness of the fastener. Creep irregularity has a great influence on the comfort of the moving train, but does not affect its running safety. When the creep amplitude is greater than 4mm, the increase in the amplitude of the creep irregularity has a greater effect on the acceleration of the car body.

Railway transportation, as an important lifeline during earthquake relief and post-disaster reconstruction, has an extremely significant role. The study of track irregularity caused by earthquakes is the basis for ensuring traffic safety after their occurrence. In this paper, a finite element model of a five-span simply supported high-speed railway beam bridge with the China Railway Track System (CRTS) II was established and an experimental verification was performed. Eighty arbitrarily selected seismic waves were extracted from the Pacific Earthquake Engineering Research Center (PEER) strong ground motion database and a nonlinear time-history analysis was performed on the finite element model. The frequency–domain distribution law of earthquake-induced track irregularities was studied. A stable target earthquake-induced track irregularity spectrum model was constructed, and its expression was fitted. According to the results, in the case of transverse earthquakes, the rails experienced noticeable alignment irregularity and cross-level irregularity, while the amplitude of the gauge and vertical irregularity were relatively small. The target irregularity spectrum has a higher amplitude in the low-frequency components. When peak ground acceleration (PGA) was low, earthquake-induced track irregularity was not obvious, but the deteriorating effects of earthquakes on track irregularities increased significantly with increasing PGA.

Dynamic vehicle–bridge interaction (VBI) plays a crucial role in the train-induced vibrations of a railway bridge for its coupling effects may reduce the bridge response and down-shift the resonant speed. The commonly used nominal theoretical resonant speed ($=f_{b}D)$ of a typical railway bridge, however, is only related to the bridge frequency ($f_b)$ and car length ($D)$, but it neglects the VBI effects of the moving trains. Such a shifted resonance phenomenon would become significant for a bridge under two trains passing by each other. This study develops a method using an equivalent modal mass to be added onto the bridge to account for the frequency shift due to the presence of multiple train cars for estimation of the shifted resonant speed. The numerical study demonstrates that the proposed method can predict the shifted resonant speed and explain the shifted-resonance phenomenon of railway bridges under train passages.

Bridge influence lines can reflect the performance status of bridge structures and are an important tool to evaluate high-speed railway bridges. Because a high-speed train can cause large dynamic response on a bridge, it is difficult to identify the static influence line of the bridge. To extract the static bridge influence lines for bridge evaluation, this paper proposes a low-pass filter design method for static influence line identification. By maximizing the difference in bridge static and dynamic energy, the relationship between the frequency domain characteristics of the bridge dynamic response and the filter parameters is established. Based on this relationship, reasonable values of the low-pass filter parameters can be determined. After filtering the dynamic response, the quasi-static response can be effectively obtained, and the bridge static influence line can be identified through the least square regularization method. Finally, a numerical example of the vehicle–bridge interaction model is used to verify the effectiveness of the proposed method. The results show that the low-pass filter designed through the proposed principle can accurately remove the dynamic effects, and its stability and robustness are good. The research results provide a reliable method for the static influence line identification of high-speed railway bridges.

In order to study the dynamic response of high-speed railway bridge and its deformation law under the coupling effect of vibration load and shield tunneling, a coupling model of shield tunneling and train load is established based on the actual case of tunneling under an adjacent bridge. The deformation characteristics and dynamic response of the bridge are investigated by analyzing the deformation under different tunneling conditions and train running speeds. The results show that the maximum disturbance of the original stress field around the bridge is caused when the shield penetrates to the near side of the bridge structure, at which time, the damping effect of the ground and bridge system on the vibration load is weakened, thus intensifying the dynamic response of the bridge system, and the additional deformation caused by the vibration load is the largest; the presence of train loads during the shield excavation slightly attenuates the differential settlement of the bridge, but increases the cumulative settlement of the bridge, in addition, the additional deformation of the bridge will increase with the increase of the train running speed; the additional deformation caused by the train load within 2m of the shield crossing on both sides of the bridge is large, so the construction should be avoided as much as possible when the train is running in this construction section.

Efficient probabilistic prediction of seismic responses is crucial for assessing the seismic-resistant capability of long-span continuous girder high-speed railway bridges. Thus, a Bayesian physics-informed neural network (BPINN) is adopted to rapidly and effectively predict the probabilistic seismic responses of such bridges. The BPINN model combines deep learning and physics to improve the accuracy and consistency of predictions, while also quantifying the uncertainties using Bayesian inference methods. Various seismic excitations, including pulse, far-field and near-field types, are employed to probabilistically predict the seismic responses of the top of bridge pier. Evaluation metrics, including mean squared error and prediction interval coverage probability, are used to assess the deterministic and probabilistic estimates of BPINN. Results demonstrate that BPINN performs better in deterministic results for far-/near-field ground motions compared to pulse-like earthquakes, with most cases exhibiting a close approximation to the 95% confidence interval. The flexibility and adaptability of BPINN in handling different types of ground motions can provide valuable insights for assessing the seismic performance of such structures.